Triple
T1267059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Labour Conference |
E15624
|
entity |
| Predicate | firstSessionHeldIn |
P28016
|
FINISHED |
| Object | 1919 |
—
|
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: 1919 | Statement: [International Labour Conference, firstSessionHeldIn, 1919]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSessionHeldIn Context triple: [International Labour Conference, firstSessionHeldIn, 1919]
-
A.
firstEditionHeldIn
Indicates the location where the first edition or initial occurrence of an event was held.
-
B.
firstSessionStart
Indicates the point in time when an entity’s very first session or interaction begins.
-
C.
officeHeldIn
Indicates that a particular office or position is held within or associated with a specific geographic or administrative location.
-
D.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
E.
convenedIn
Indicates that an event, meeting, or formal gathering was brought together and held at a specific location.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c037f14c8190baa42f70f8846583 |
completed | March 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:50 p.m.