Triple
T31450311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abba Salama |
E802303
|
entity |
| Predicate | capturedInYouth |
P171889
|
FINISHED |
| Object | Red Sea region |
—
|
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: Red Sea region | Statement: [Abba Salama, capturedInYouth, Red Sea region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capturedInYouth Context triple: [Abba Salama, capturedInYouth, Red Sea region]
-
A.
capturedIn
Indicates that one entity was taken prisoner, seized, or otherwise brought under control within the context, location, or event represented by another entity.
-
B.
capturedBy
Indicates that one entity has been seized, taken into control, or otherwise apprehended by another entity.
-
C.
youthPlayer
Indicates a relationship where an individual is a member of, or plays for, the youth or junior division of a team, club, or organization.
-
D.
capturedDuring
Indicates that one event or state occurred within the temporal span of another, typically representing that something was recorded, seized, or documented while a specific situation or activity was taking place.
-
E.
capturedAtAge
Indicates the age an entity was when it was captured.
- 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_69f348c5a6bc819092a557e95438976f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a5f656ec81909e02b0b873303adf |
completed | May 3, 2026, 1:33 a.m. |
Created at: April 30, 2026, 9:12 p.m.