Triple
T19363249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikohabad |
E484332
|
entity |
| Predicate | distanceTo |
P350
|
FINISHED |
| Object | Firozabad |
—
|
NE NERFINISHED |
How this triple was built (2 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: Firozabad | Statement: [Shikohabad, distanceTo, Firozabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Firozabad Context triple: [Shikohabad, distanceTo, Firozabad]
-
A.
Firozabad
chosen
Firozabad is an Indian city in Uttar Pradesh renowned for its glass and bangle industry.
-
B.
Ferozabad
Ferozabad is a residential and commercial neighborhood located within the Karachi East District of Karachi, Pakistan.
-
C.
Farrukhabad
Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
-
D.
Shahjahanpur
Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
-
E.
Moradabad
Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e619a897008190a2c62a50ca60de2d |
completed | April 20, 2026, 12:18 p.m. |
Created at: April 10, 2026, 1:34 p.m.