Triple
T7306516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamshedpur industrial region |
E167987
|
entity |
| Predicate | majorCompany |
P597
|
FINISHED |
| Object |
Tata Tinplate
Tata Tinplate is a leading Indian manufacturer of tinplate and tin-free steel, primarily serving the packaging and canning industries.
|
E655823
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tata Tinplate | Statement: [Jamshedpur industrial region, majorCompany, Tata Tinplate]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tata Tinplate Context triple: [Jamshedpur industrial region, majorCompany, Tata Tinplate]
-
A.
Tata
Tata is the nickname of Gerardo "Tata" Martino, an Argentine football manager and former player known for coaching top clubs and national teams, including FC Barcelona, Argentina, and Mexico.
-
B.
Tata
Tata is a small town and oasis in southern Morocco, known as a gateway to the Anti-Atlas mountains and the surrounding desert landscapes.
-
C.
Tata
Tata is a historic Hungarian town in Komárom-Esztergom County known for its lakes, castles, and natural surroundings.
-
D.
Aluminium Konin
Aluminium Konin is a Polish football club known for competing in the lower tiers of the national league system.
-
E.
Hillenbrand
Hillenbrand is a surname of German origin borne by various notable individuals in fields such as diplomacy, literature, and sports.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tata Tinplate Triple: [Jamshedpur industrial region, majorCompany, Tata Tinplate]
Generated description
Tata Tinplate is a leading Indian manufacturer of tinplate and tin-free steel, primarily serving the packaging and canning industries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tata Tinplate Target entity description: Tata Tinplate is a leading Indian manufacturer of tinplate and tin-free steel, primarily serving the packaging and canning industries.
-
A.
Tata
Tata is the nickname of Gerardo "Tata" Martino, an Argentine football manager and former player known for coaching top clubs and national teams, including FC Barcelona, Argentina, and Mexico.
-
B.
Tata
Tata is a small town and oasis in southern Morocco, known as a gateway to the Anti-Atlas mountains and the surrounding desert landscapes.
-
C.
Tata
Tata is a historic Hungarian town in Komárom-Esztergom County known for its lakes, castles, and natural surroundings.
-
D.
Aluminium Konin
Aluminium Konin is a Polish football club known for competing in the lower tiers of the national league system.
-
E.
Hillenbrand
Hillenbrand is a surname of German origin borne by various notable individuals in fields such as diplomacy, literature, and sports.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebd7dcf88190b3e66bea327fc63d |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e56443b08190aee2c26633cdcbed |
completed | March 28, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_69c7e97659a08190a548beda4d7d6d9f |
completed | March 28, 2026, 2:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ea1847008190aae44d6eb9f572d4 |
completed | March 28, 2026, 2:47 p.m. |
Created at: March 27, 2026, 3:01 p.m.