Triple
T30220476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Travel Bookshop |
E768329
|
entity |
| Predicate | portrayedByOwnerActor |
P1507
|
FINISHED |
| Object | Hugh Grant |
E36287
|
NE 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: Hugh Grant | Statement: [The Travel Bookshop, portrayedByOwnerActor, Hugh Grant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByOwnerActor Context triple: [The Travel Bookshop, portrayedByOwnerActor, Hugh Grant]
-
A.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
B.
portrayedBySpeciesActor
Indicates that an entity is depicted or represented by an actor belonging to a particular species.
-
C.
portrayedBySource
Indicates that an entity is depicted or represented by a particular source, such as a specific image, document, or media item.
-
D.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
E.
portrayedByCharacterType
Indicates that an entity is depicted or represented by a character of a specified type (e.g., hero, villain, sidekick) in a narrative or media work.
- F. None of above.
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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a27643d4b8c81908cae65b88f089b37 |
completed | June 9, 2026, 12:54 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
Created at: April 29, 2026, 7:35 p.m.