Triple
T5933832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelin |
E131996
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
|
E555277
|
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: Tigar | Statement: [Michelin, hasSubsidiary, Tigar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tigar Context triple: [Michelin, hasSubsidiary, Tigar]
-
A.
Tig
Tig is a fictional character from the television series "Sons of Anarchy," known for his volatile personality and loyalty to the motorcycle club.
-
B.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
-
C.
Tiger
The tiger is a large, powerful carnivorous cat known for its distinctive orange coat with black stripes and its status as an apex predator in Asia.
-
D.
Tiger
Tiger is a legendary American professional golfer widely regarded as one of the greatest players in the history of the sport.
-
E.
Grandpere Tiger
Grandpere Tiger is a gentle, French-accented tiger character from the Neighborhood of Make-Believe on the children's television series "Mister Rogers' Neighborhood."
- 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: Tigar Triple: [Michelin, hasSubsidiary, Tigar]
Generated description
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tigar Target entity description: Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
-
A.
Tig
Tig is a fictional character from the television series "Sons of Anarchy," known for his volatile personality and loyalty to the motorcycle club.
-
B.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
-
C.
Tiger
The tiger is a large, powerful carnivorous cat known for its distinctive orange coat with black stripes and its status as an apex predator in Asia.
-
D.
Tiger
Tiger is a legendary American professional golfer widely regarded as one of the greatest players in the history of the sport.
-
E.
Grandpere Tiger
Grandpere Tiger is a gentle, French-accented tiger character from the Neighborhood of Make-Believe on the children's television series "Mister Rogers' Neighborhood."
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0389f6fc881909527b928838ffcdd |
completed | March 22, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c064d2a4819096085668182cfde1 |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c109b3288190928dc4539a2872c2 |
completed | March 23, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c1f6fe60819080a00976740b6a9c |
completed | March 23, 2026, 4:30 a.m. |
Created at: March 22, 2026, 4 p.m.