Triple
T11171446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Dane |
E264281
|
entity |
| Predicate | isTypecast |
P98242
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Alexander Dane, isTypecast, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypecast Context triple: [Alexander Dane, isTypecast, true]
-
A.
hasCastType
Indicates that an entity participates in a production with a specified type of casting role (e.g., lead, supporting, cameo).
-
B.
hasCasting
Indicates that an entity features a particular actor or set of actors in its cast.
-
C.
castingType
Indicates the specific method or category of casting used to transform or represent one entity in terms of another.
-
D.
castFrom
Indicates that one entity is transformed or converted from another, typically changing its type or representation while preserving its underlying value or identity.
-
E.
hasMinimalCast
Indicates that an entity (such as a film or production) involves only a small or minimal number of cast members.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e89660208190b1d9e91529f5d246 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.