Triple
T14748659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark Star Trilogy |
E346539
|
entity |
| Predicate | awardsReceivedByFirstVolume |
P115632
|
FINISHED |
| Object | finalist for the 2019 National Book Award for Fiction |
—
|
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: finalist for the 2019 National Book Award for Fiction | Statement: [Dark Star Trilogy, awardsReceivedByFirstVolume, finalist for the 2019 National Book Award for Fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardsReceivedByFirstVolume Context triple: [Dark Star Trilogy, awardsReceivedByFirstVolume, finalist for the 2019 National Book Award for Fiction]
-
A.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
B.
awardedForFirstTimeTo
Indicates that an entity receives an award or recognition for the very first time.
-
C.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
D.
hasMultipleAwardsIndicatedBy
Indicates that an entity is recognized as having received multiple awards, as evidenced or signaled by a specified source or indicator.
-
E.
awardsAre
Indicates that one entity confers or grants awards or honors to another entity.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d2e1748190b16ede681fe52872 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.