Triple
T36923859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | For and Against |
E913280
|
entity |
| Predicate | usedAsMeaningOf |
P10718
|
FINISHED |
| Object | Women; or, Pour et Contre |
—
|
NE NERFINISHED |
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: Women; or, Pour et Contre | Statement: [For and Against, usedAsMeaningOf, Women; or, Pour et Contre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsMeaningOf Context triple: [For and Against, usedAsMeaningOf, Women; or, Pour et Contre]
-
A.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
B.
possibleMeaning
chosen
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
C.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
D.
pluralUsageMeaning
Indicates that the meaning or interpretation of an expression depends on its use in a plural rather than singular context.
-
E.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: May 3, 2026, 4:13 p.m.