Triple
T35412592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nahila |
E1023550
|
entity |
| Predicate | fictionalEthnicIdentity |
P178064
|
FINISHED |
| Object | Palestinian |
—
|
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: Palestinian | Statement: [Nahila, fictionalEthnicIdentity, Palestinian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalEthnicIdentity Context triple: [Nahila, fictionalEthnicIdentity, Palestinian]
-
A.
fictionalEthnoCulturalIdentity
Indicates that an entity is associated with an invented or imaginary ethnic or cultural identity, rather than a real-world one.
-
B.
fictionalEthnicFocus
Indicates that something is primarily concerned with, centered on, or thematically emphasizes a fictional or invented ethnic group.
-
C.
fictionalRegionalIdentity
Indicates that an entity is associated with, or characterized by, an invented or imaginary regional or local identity.
-
D.
hasEthnicityInFiction
chosen
Indicates that a fictional character or entity is portrayed as having a particular ethnicity within a narrative or fictional context.
-
E.
fictionalCitizenship
Indicates that an entity is recognized as a citizen of a fictional or imaginary polity, realm, or jurisdiction.
- 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_69f76df54bac8190bd0d3b0eb35cda5f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff136ed2a881908f713401083970d1 |
completed | May 9, 2026, 10:58 a.m. |
| PD | Predicate disambiguation | batch_69ff10f9e3448190b6cb6ea5a67713c1 |
completed | May 9, 2026, 10:48 a.m. |
Created at: May 3, 2026, 4:03 p.m.