Triple
T34373212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabennisi |
E882217
|
entity |
| Predicate | hasGenderOfMainCommunity |
P62762
|
FINISHED |
| Object | male |
—
|
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: male | Statement: [Tabennisi, hasGenderOfMainCommunity, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderOfMainCommunity Context triple: [Tabennisi, hasGenderOfMainCommunity, male]
-
A.
genderOfResidents
chosen
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
B.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
C.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
D.
genderOfMembers
Indicates the gender or genders associated with the members of a group or organization.
-
E.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
Created at: May 1, 2026, 1:59 a.m.