Triple
T5079242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amity boat tours |
E114473
|
entity |
| Predicate | fictionalService |
P61295
|
FINISHED |
| Object | harbor sightseeing tours |
—
|
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: harbor sightseeing tours | Statement: [Amity boat tours, fictionalService, harbor sightseeing tours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalService Context triple: [Amity boat tours, fictionalService, harbor sightseeing tours]
-
A.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
-
B.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
C.
serviceFor
Indicates that one entity provides a service or performs functions on behalf of another entity.
-
D.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
E.
setInFictionalOrganization
Indicates that an entity is located within, associated with, or takes place inside a fictional organization.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74f75cf0819088be9e076eaf3168 |
completed | March 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73d90b608190bd6c2407e84e2b64 |
completed | March 20, 2026, 4:20 p.m. |
Created at: March 20, 2026, 1:39 p.m.