Triple
T9169826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gender Inequality Index |
E220053
|
entity |
| Predicate | worstValueMeaning |
P86607
|
FINISHED |
| Object | 1 indicates extreme gender inequality |
—
|
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: 1 indicates extreme gender inequality | Statement: [Gender Inequality Index, worstValueMeaning, 1 indicates extreme gender inequality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worstValueMeaning Context triple: [Gender Inequality Index, worstValueMeaning, 1 indicates extreme gender inequality]
-
A.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
B.
overallMeaning
Indicates the general or overarching significance, interpretation, or message conveyed by something as a whole.
-
C.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
D.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
E.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaae23f048190847f12317be925b1 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc66d7bf648190b8bff5b584b84975 |
completed | April 1, 2026, 12:29 a.m. |
Created at: March 30, 2026, 7:22 p.m.