Triple
T11675586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mughal Subah of Bihar |
E277482
|
entity |
| Predicate | importantCity |
P3940
|
FINISHED |
| Object | Munger |
E295114
|
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: Munger | Statement: [Mughal Subah of Bihar, importantCity, Munger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Munger Context triple: [Mughal Subah of Bihar, importantCity, Munger]
-
A.
Munger
chosen
Munger is a historic city in the eastern Indian state of Bihar, known for its ancient fort, spiritual centers, and traditional gun-making industry.
-
B.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
C.
Mackenzell
Mackenzell is a small village in the Hesse region of central Germany.
-
D.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
-
E.
Berggruen
Berggruen is a surname most prominently associated with the billionaire investor and philanthropist Nicholas Berggruen and his family.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a44504c48190b519765a83ff9c5e |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef13f12c2481909171a3237064c76d |
completed | April 27, 2026, 7:44 a.m. |
Created at: April 8, 2026, 9:40 p.m.