Triple
T30575964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Slater as Daniel Molloy |
E778244
|
entity |
| Predicate | narrativeTimeSpanRecorded |
P11197
|
FINISHED |
| Object | centuries of Louis’s life |
—
|
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: centuries of Louis’s life | Statement: [Christian Slater as Daniel Molloy, narrativeTimeSpanRecorded, centuries of Louis’s life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrativeTimeSpanRecorded Context triple: [Christian Slater as Daniel Molloy, narrativeTimeSpanRecorded, centuries of Louis’s life]
-
A.
timeOfNarrative
chosen
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
B.
narrativeTimeSpanHours
Indicates the duration of a narrative or story event measured in hours.
-
C.
narrativeMoment
Indicates the specific point or phase within a narrative at which an event, action, or relationship occurs.
-
D.
timeRecorded
Indicates that a specific point or period in time has been captured and stored as associated with an event, action, or state.
-
E.
recorded
Indicates that one entity captured, stored, or documented information, audio, video, or data about another entity or event.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 29, 2026, 8:22 p.m.