Triple
T33732071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orion |
E864298
|
entity |
| Predicate | totalSurfaceStayTime_hours |
P43134
|
FINISHED |
| Object | 71 |
—
|
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: 71 | Statement: [Orion, totalSurfaceStayTime_hours, 71]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalSurfaceStayTime_hours Context triple: [Orion, totalSurfaceStayTime_hours, 71]
-
A.
stayDurationFocus
Indicates the length of time an entity remains at or engaged with a particular place, activity, or context as the primary focus.
-
B.
hasResidenceTime
Indicates the duration for which something remains or stays within a particular place, system, or state.
-
C.
durationTotal
chosen
Indicates the overall length of time for which an event, process, or state persists, typically aggregating all its constituent durations.
-
D.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
-
E.
venueResidencyLengthNights
Indicates the number of nights an entity stays or is scheduled to stay at a particular venue.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 1, 2026, 1:44 a.m.