Triple
T30218512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ULF1.1 |
E768273
|
entity |
| Predicate | relatedShuttleFlight |
P67178
|
FINISHED |
| Object | STS-121 |
E213285
|
NE 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: STS-121 | Statement: [ULF1.1, relatedShuttleFlight, STS-121]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedShuttleFlight Context triple: [ULF1.1, relatedShuttleFlight, STS-121]
-
A.
airTravelRelationWith
Indicates a relationship where one entity travels to, from, or between locations by air (e.g., via airplane or other aircraft) in connection with another entity.
-
B.
associatedFlightType
Indicates a relationship where one entity is linked to, or characterized by, a particular type or category of flight.
-
C.
connectsTravelBetween
Indicates a relationship where something (such as a route, service, or mode of transport) enables or provides travel between two locations.
-
D.
involvedTravelBetween
Indicates a relationship where an entity participates in or is associated with travel occurring between two specified locations.
-
E.
associatedWithFlight
chosen
Indicates a relationship where an entity is linked or connected to a specific flight, such as by participation, operation, or relevance.
- F. None of above.
Provenance (4 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0212b3462c8190ba3587852cb10655 |
completed | May 11, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a27643d4b8c81908cae65b88f089b37 |
completed | June 9, 2026, 12:54 a.m. |
| PD | Predicate disambiguation | batch_6a020f3138a48190ac630e810939e881 |
completed | May 11, 2026, 5:17 p.m. |
Created at: April 29, 2026, 7:34 p.m.