Triple
T3858038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People's Front for Democracy and Justice |
E90065
|
entity |
| Predicate | womenWingStatus |
P9030
|
FINISHED |
| Object | party-affiliated |
—
|
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: party-affiliated | Statement: [People's Front for Democracy and Justice, womenWingStatus, party-affiliated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenWingStatus Context triple: [People's Front for Democracy and Justice, womenWingStatus, party-affiliated]
-
A.
womenWing
Indicates a relationship where a woman is associated with or positioned at the wing (side section) of a structure, group, or setting.
-
B.
womensWing
chosen
Indicates a relationship where an entity is designated as the women’s section or women-only wing of a larger place or facility.
-
C.
womenStatus
Indicates the social, legal, economic, or cultural position or condition assigned to women within a given context or system.
-
D.
wearerStatus
Indicates the condition or role of an entity in its capacity as a wearer of something (e.g., clothing, equipment, or an accessory).
-
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.
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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1e68f88190941c39221486f6ae |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.