Triple
T5918464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Struggle in the Valley |
E131639
|
entity |
| Predicate | hasCastRole |
P36975
|
FINISHED |
| Object | Faten Hamama as female lead |
—
|
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: Faten Hamama as female lead | Statement: [Struggle in the Valley, hasCastRole, Faten Hamama as female lead]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCastRole Context triple: [Struggle in the Valley, hasCastRole, Faten Hamama as female lead]
-
A.
hasPlayedRole
chosen
Indicates that an entity has performed or portrayed a particular role or character in some context (such as a film, play, or production).
-
B.
hasCrewRole
Indicates that an entity serves in a specific role or position within a crew associated with another entity.
-
C.
hasInUniverseRole
Indicates that an entity holds or performs a specific role or function within a particular fictional or defined universe.
-
D.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
E.
hasMainRole
Indicates that an entity holds the primary or most significant role in relation to another entity or context.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c048fc112c8190b905bf561c9de096 |
completed | March 22, 2026, 7:54 p.m. |
| PD | Predicate disambiguation | batch_69c03352208c8190968efed05a9fd416 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.