Triple
T191121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestinian American |
E3722
|
entity |
| Predicate | hasNotableProfessionDistributionIn |
P7846
|
FINISHED |
| Object | academia |
—
|
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: academia | Statement: [Palestinian American, hasNotableProfessionDistributionIn, academia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProfessionDistributionIn Context triple: [Palestinian American, hasNotableProfessionDistributionIn, academia]
-
A.
hasNotableMember
Indicates that a group, organization, or collection includes at least one member who is distinguished or noteworthy in some significant way.
-
B.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
-
C.
hasNotableHonoree
Indicates that an entity is notably dedicated to, named after, or honors a particular person or group.
-
D.
hasNotableComposer
Indicates that an entity is associated with a composer who is recognized as particularly significant or distinguished.
-
E.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a258fbd18881908c9d40f7a2480945 |
completed | Feb. 28, 2026, 2:54 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.