Triple
T12748542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koregaon Bhima |
E304671
|
entity |
| Predicate | memorialInscriptionLanguage |
P15804
|
FINISHED |
| Object | English |
—
|
LITERAL 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: English | Statement: [Koregaon Bhima, memorialInscriptionLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorialInscriptionLanguage Context triple: [Koregaon Bhima, memorialInscriptionLanguage, English]
-
A.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
B.
hasLanguageOnPlaque
Indicates that a specific language appears in the text or inscription displayed on a particular plaque.
-
C.
secondaryLanguageOfInscriptions
Indicates that a specified language serves as the secondary language used in the inscriptions associated with a given entity.
-
D.
languageOfCommemoration
Indicates the language used to express or perform the act of commemoration.
-
E.
bellInscriptionLanguage
Indicates the language in which the inscription on a bell is written.
- F. None of above.
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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.