Triple
T23089857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 101st Air Refueling Squadron |
E575714
|
entity |
| Predicate | missionEffect |
P23809
|
FINISHED |
| Object | extend range of military aircraft |
—
|
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: extend range of military aircraft | Statement: [101st Air Refueling Squadron, missionEffect, extend range of military aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: missionEffect Context triple: [101st Air Refueling Squadron, missionEffect, extend range of military aircraft]
-
A.
mission
Indicates that an entity is assigned or engaged in a specific task, operation, or purpose-directed undertaking.
-
B.
notableEffect
chosen
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
C.
ultimateEffect
Indicates the final or overall outcome that results from a preceding action, condition, or sequence of events.
-
D.
attackEffect
Indicates that one entity’s attack produces a specific effect or consequence on another entity.
-
E.
tierEffect
Indicates how belonging to a particular tier influences or modifies the outcome, behavior, or properties associated with that tier.
- 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18da8818481908d768a0462f3f837 |
completed | April 29, 2026, 4:48 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:57 p.m.