Triple
T28696333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Hilal Benghazi |
E729425
|
entity |
| Predicate | homeCityRole |
P167927
|
FINISHED |
| Object | represents Benghazi in Libyan football |
—
|
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: represents Benghazi in Libyan football | Statement: [Al-Hilal Benghazi, homeCityRole, represents Benghazi in Libyan football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCityRole Context triple: [Al-Hilal Benghazi, homeCityRole, represents Benghazi in Libyan football]
-
A.
homeCityOf
Indicates that a particular city is the primary place of residence or origin for a given person or organization.
-
B.
homeCityInBackstory
Indicates that an entity has a specified city as its home city within its narrative or character backstory.
-
C.
homeCityInStory
Indicates that a specified city serves as a character’s home city within the context of a particular story.
-
D.
homeCityPopulationRole
Indicates that an entity’s role or status is defined in relation to the population size of its home city.
-
E.
homeCityMetropolitanArea
Indicates that a specified city serves as the primary metropolitan area associated with a given entity’s home location.
- 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_69f043e6e9688190b6bdd6e5665498ff |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 5:39 a.m.