Triple
T37561742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Steele (paratrooper) |
E933839
|
entity |
| Predicate | parachuteDropZone |
P142315
|
FINISHED |
| Object | Sainte-Mère-Église |
—
|
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: Sainte-Mère-Église | Statement: [John Steele (paratrooper), parachuteDropZone, Sainte-Mère-Église]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parachuteDropZone Context triple: [John Steele (paratrooper), parachuteDropZone, Sainte-Mère-Église]
-
A.
parachuteSystem
Indicates that one entity functions as a parachute system used to safely decelerate or recover another entity.
-
B.
skydivingDropZone
chosen
Indicates a location that serves as the designated area where skydivers are intended to land after a jump.
-
C.
parachuteStatus
Indicates the current condition or operational state of a parachute in relation to its use or deployment.
-
D.
parachuteType
Indicates the specific kind or category of parachute associated with an entity or event.
-
E.
parachuteMass
Indicates the mass or weight associated with a parachute in the described context.
- 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_69f76ecb4acc8190b53f96d0b013e415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba61dff5081909fec88a7aeb0c8a1 |
completed | May 6, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69fba350e9a8819095893229d9643572 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.