Triple
T7999035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pan Africanist Women’s Organization |
E186197
|
entity |
| Predicate | hasWingOf |
P80253
|
FINISHED |
| Object | Pan Africanist Congress women members |
—
|
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: Pan Africanist Congress women members | Statement: [Pan Africanist Women’s Organization, hasWingOf, Pan Africanist Congress women members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWingOf Context triple: [Pan Africanist Women’s Organization, hasWingOf, Pan Africanist Congress women members]
-
A.
hasWings
Indicates that an entity possesses wings as physical appendages.
-
B.
hasHostWing
Indicates that one entity serves as the host structure or supporting wing for another entity.
-
C.
hadWing
Indicates that an entity possessed one or more wings at some point in time.
-
D.
hasNumberOfLeftWings
Indicates the quantity of left wings that an entity possesses.
-
E.
hasWingConfiguration
Indicates how an entity’s wings are arranged, structured, or configured relative to its body or to each other.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c9a12788190a5607a538f4e07c1 |
completed | March 31, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:17 p.m.