Triple
T37561741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Steele (paratrooper) |
E933839
|
entity |
| Predicate | entangledOn |
P91259
|
FINISHED |
| Object | church steeple of 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: church steeple of Sainte-Mère-Église | Statement: [John Steele (paratrooper), entangledOn, church steeple of Sainte-Mère-Église]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entangledOn Context triple: [John Steele (paratrooper), entangledOn, church steeple of Sainte-Mère-Église]
-
A.
entangledWith
Indicates a mutual state in which two or more entities are so interconnected that a change or condition in one inherently affects or constrains the other(s).
-
B.
canBeEntangledIn
chosen
Indicates that one entity is capable of becoming physically or conceptually caught, intertwined, or ensnared within another entity or situation.
-
C.
engagedOn
Indicates that two entities are committed to be married to each other as of a specific date or point in time.
-
D.
engagedTo
Indicates that two entities are formally committed to marry each other.
-
E.
bondedWith
Indicates that two entities are joined by a strong, enduring connection or attachment, whether emotional, social, or structural.
- 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.