Triple
T1162043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Chelmsford |
E24513
|
entity |
| Predicate | officeHeldDuring |
P25646
|
FINISHED |
| Object | Viceroy of India during World War I |
—
|
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: Viceroy of India during World War I | Statement: [Lord Chelmsford, officeHeldDuring, Viceroy of India during World War I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldDuring Context triple: [Lord Chelmsford, officeHeldDuring, Viceroy of India during World War I]
-
A.
convenesDuring
Indicates that one entity formally gathers or brings together another entity or group during a specified time period or event.
-
B.
typicallyHeldIn
Indicates that an event, activity, or process most commonly or usually takes place within a particular location, venue, or context.
-
C.
positionHeld
Indicates that an entity occupies or has occupied a specific role, job, office, or position within an organization or context.
-
D.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
E.
officeHeldByAuthor
Indicates that a particular office or official position is/was occupied or held by a specific author.
- F. None of above. chosen
Provenance (4 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcb2bb84819088bd94e91c10fb0c |
completed | March 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69a4bb525b648190adcb7a29256d3c41 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:45 p.m.