Triple
T32616190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Tango |
E833790
|
entity |
| Predicate | usedForTravelBetween |
P148000
|
FINISHED |
| Object | Seattle |
—
|
NE NERFINISHED |
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: Seattle | Statement: [Charlie Tango, usedForTravelBetween, Seattle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForTravelBetween Context triple: [Charlie Tango, usedForTravelBetween, Seattle]
-
A.
involvedTravelBetween
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified locations.
-
B.
connectsTravelBetween
chosen
Indicates a relationship where something (such as a route, service, or mode of transport) enables or provides travel between two locations.
-
C.
facilitatesTravelWithin
Indicates that one entity enables or makes it easier for another entity to move or travel within a specific area or region.
-
D.
usedBetweenStations
Indicates that something (such as a service, route, or resource) is utilized in the context of travel or operation between two stations.
-
E.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:06 a.m.