Triple
T38363365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hollywood Palace (appearances) |
E892356
|
entity |
| Predicate | recurringRoleType |
P5518
|
FINISHED |
| Object | featured dancer |
—
|
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: featured dancer | Statement: [The Hollywood Palace (appearances), recurringRoleType, featured dancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringRoleType Context triple: [The Hollywood Palace (appearances), recurringRoleType, featured dancer]
-
A.
hasRecurringRole
Indicates that an entity repeatedly appears or participates in a role within an ongoing or multiple related contexts over time.
-
B.
repetitionRole
Indicates that one entity serves a specific function or role within a repeated or recurring occurrence of another entity or event.
-
C.
typeOfRole
chosen
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
D.
representedRole
Indicates that one entity serves as a stand-in, proxy, or representative performing a role on behalf of another entity.
-
E.
profileRole
Indicates the specific role or function an entity holds within a given profile or contextual configuration.
- 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_69f76e47cb4c8190bdd92cd1db59c0c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:31 p.m.