Triple
T2679488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sparta |
E56539
|
entity |
| Predicate | womenStatus |
P42182
|
FINISHED |
| Object | relatively high property rights for 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: relatively high property rights for women | Statement: [Sparta, womenStatus, relatively high property rights for women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenStatus Context triple: [Sparta, womenStatus, relatively high property rights for women]
-
A.
genderEquality
Indicates that the relationship or action promotes, reflects, or ensures equal rights, opportunities, and treatment for all genders without discrimination.
-
B.
admittedWomen
Indicates that an entity allowed or accepted women into a place, group, institution, or event.
-
C.
womenWing
Indicates a relationship where a woman is associated with or positioned at the wing (side section) of a structure, group, or setting.
-
D.
hasWomenOrganization
Indicates that an entity is associated with, contains, or is part of an organization specifically for women.
-
E.
hadWomenOrganization
Indicates that an entity was associated with or involved in an organization focused on women or women’s issues.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda2dc5788190b4b83cb9ed08266c |
completed | March 7, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:54 p.m.