Triple
T14848057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bounty (1983 film replica ship) |
E349152
|
entity |
| Predicate | hasEraRepresented |
P36399
|
FINISHED |
| Object | late 18th century |
—
|
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: late 18th century | Statement: [Bounty (1983 film replica ship), hasEraRepresented, late 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEraRepresented Context triple: [Bounty (1983 film replica ship), hasEraRepresented, late 18th century]
-
A.
representsEra
chosen
Indicates that one entity designates the historical era, period, or age to which another entity belongs or is associated.
-
B.
playedWithEra
Indicates that an entity performed or was active during a specified historical or stylistic era.
-
C.
hasPrimaryEra
Indicates that an entity is chiefly associated with or belongs to a particular historical or temporal era.
-
D.
appliesToEra
Indicates that something is relevant, valid, or in effect during a particular historical or temporal era.
-
E.
partOfEra
Indicates that one entity exists as a temporal segment or component within the duration or scope of a larger historical era.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:53 a.m.