Triple
T13702358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G.I. Jane |
E328550
|
entity |
| Predicate | fictionalFocus |
P111228
|
FINISHED |
| Object | first woman in U.S. Navy SEALs training |
—
|
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: first woman in U.S. Navy SEALs training | Statement: [G.I. Jane, fictionalFocus, first woman in U.S. Navy SEALs training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalFocus Context triple: [G.I. Jane, fictionalFocus, first woman in U.S. Navy SEALs training]
-
A.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
B.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
C.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
-
D.
fictionalTheme
Indicates that a work, element, or context is centered around or characterized by a fictional theme or motif.
-
E.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
- F. None of above. chosen
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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad162158819089280ee1e6b5c2cf |
completed | April 13, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:54 p.m.