Triple
T3801043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Thousand-Mile Walk to the Gulf |
E91687
|
entity |
| Predicate | timeOfJourney |
P29135
|
FINISHED |
| Object | 1867 |
—
|
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: 1867 | Statement: [A Thousand-Mile Walk to the Gulf, timeOfJourney, 1867]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfJourney Context triple: [A Thousand-Mile Walk to the Gulf, timeOfJourney, 1867]
-
A.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
B.
voyageDuration
chosen
Indicates the length of time that a voyage or journey lasts from its start to its end.
-
C.
flightDuration
Indicates the length of time that a specific flight takes from departure to arrival.
-
D.
travelTimeTypical
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
E.
timeTravelFrom
Indicates a relationship where an entity initiates time travel starting from a specific time or temporal location.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.