Triple
T17312209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy members |
E420325
|
entity |
| Predicate | historicalBiasCriticism |
P805
|
FINISHED |
| Object | underrepresentation of women |
—
|
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: underrepresentation of women | Statement: [Academy members, historicalBiasCriticism, underrepresentation of women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalBiasCriticism Context triple: [Academy members, historicalBiasCriticism, underrepresentation of women]
-
A.
hasCriticism
Indicates that one entity expresses disapproval, objection, or negative evaluation directed toward another entity.
-
B.
historicallyConsidered
Indicates that one entity has been regarded or classified in a particular way relative to another entity during a past historical period.
-
C.
historicalReception
Indicates how an event, work, or figure was received, interpreted, or evaluated by people and institutions over time.
-
D.
criticizedFor
chosen
Indicates that one entity expresses disapproval or negative judgment of another entity specifically because of a particular action, quality, or outcome.
-
E.
historicallyChallengingFor
Indicates that one entity has posed significant difficulties, obstacles, or problems for another over an extended historical period.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439993bac8190a72f6af529bd7cce |
completed | April 19, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b01b9d1c8190a406dd941c9b11a1 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:43 a.m.