Triple
T27840695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emmett Brown |
E703669
|
entity |
| Predicate | timePeriodTraveledTo |
P161451
|
FINISHED |
| Object | 1955 |
—
|
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: 1955 | Statement: [Emmett Brown, timePeriodTraveledTo, 1955]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodTraveledTo Context triple: [Emmett Brown, timePeriodTraveledTo, 1955]
-
A.
traveledFor
Indicates that an entity moved or journeyed to a place or event for a specific purpose, reason, or activity.
-
B.
timeOfJourneyDescribed
chosen
Indicates that the predicate specifies the particular time period or duration during which the described journey takes place.
-
C.
timeTravelFrom
Indicates a relationship where an entity initiates time travel starting from a specific time or temporal location.
-
D.
distanceTraveled
Indicates the total length of the path an entity has moved over a period of time or between two points.
-
E.
traveledYears
Indicates the number of years an entity has spent traveling or engaged in travel-related activity.
- 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_69ef840d9e3c819093615ebff4ec22be |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 27, 2026, 6:02 p.m.