Triple
T5129922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umaria |
E115670
|
entity |
| Predicate | nearestMajorCity |
P1982
|
FINISHED |
| Object | Katni |
E102807
|
NE FINISHED |
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: Katni | Statement: [Umaria, nearestMajorCity, Katni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katni Context triple: [Umaria, nearestMajorCity, Katni]
-
A.
Katni
chosen
Katni is an industrial city in central India known for its cement factories, railway junction, and marble and limestone mining.
-
B.
Katni Junction
Katni Junction is a major railway junction in Madhya Pradesh, India, serving as an important connecting hub for multiple rail routes across central and northern India.
-
C.
District 12
District 12 is a regional division of Caltrans responsible for planning, constructing, and maintaining the state highway system in Orange County, California.
-
D.
Keoma
Keoma is a 1976 Italian spaghetti Western film directed by Enzo G. Castellari, widely regarded as one of Franco Nero’s most iconic and atmospheric roles.
-
E.
Toma
Toma is a major Mande language spoken primarily in Guinea and neighboring West African countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7827c764819086da3b79f2020224 |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4c23d5c8190883a297254d9c80d |
completed | March 21, 2026, 4:18 p.m. |
Created at: March 20, 2026, 1:42 p.m.