Triple
T16062218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fatehabad district |
E389638
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Tohana
Tohana is a town and municipal council in the Fatehabad district of the Indian state of Haryana, known as an agricultural and trading center in the region.
|
E1201002
|
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: Tohana | Statement: [Fatehabad district, hasSettlement, Tohana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tohana Context triple: [Fatehabad district, hasSettlement, Tohana]
-
A.
Shinasha
Shinasha is a North Omotic language spoken by the Shinasha people of western Ethiopia.
-
B.
Takabisha
Takabisha is a record-breaking steel roller coaster in Japan renowned for its extremely steep drop and intense thrill elements.
-
C.
Shinkiari
Shinkiari is a town in Pakistan’s Khyber Pakhtunkhwa province, known for its agricultural surroundings and its location along the Karakoram Highway near Mansehra.
-
D.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
-
E.
Takeno
Takeno was a former town in Hyōgo Prefecture, Japan, that became part of the expanded city of Toyooka following a municipal merger.
- 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: Tohana Triple: [Fatehabad district, hasSettlement, Tohana]
Generated description
Tohana is a town and municipal council in the Fatehabad district of the Indian state of Haryana, known as an agricultural and trading center in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tohana Target entity description: Tohana is a town and municipal council in the Fatehabad district of the Indian state of Haryana, known as an agricultural and trading center in the region.
-
A.
Shinasha
Shinasha is a North Omotic language spoken by the Shinasha people of western Ethiopia.
-
B.
Takabisha
Takabisha is a record-breaking steel roller coaster in Japan renowned for its extremely steep drop and intense thrill elements.
-
C.
Shinkiari
Shinkiari is a town in Pakistan’s Khyber Pakhtunkhwa province, known for its agricultural surroundings and its location along the Karakoram Highway near Mansehra.
-
D.
Takanot
Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
-
E.
Takeno
Takeno was a former town in Hyōgo Prefecture, Japan, that became part of the expanded city of Toyooka following a municipal merger.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837a04108190b5a1dbbe2063039e |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00077c8e2881909a11a4c53691d187 |
completed | May 10, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_6a000a96d71881909dc1736b7fd6ac3e |
completed | May 10, 2026, 4:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a000af74b448190bef37fbe3a70fedd |
completed | May 10, 2026, 4:35 a.m. |
Created at: April 10, 2026, 4:57 a.m.