Triple
T20191653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucina |
E492990
|
entity |
| Predicate | fighterType |
P139073
|
FINISHED |
| Object | echo-style fighter of Marth in Super Smash Bros. |
—
|
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: echo-style fighter of Marth in Super Smash Bros. | Statement: [Lucina, fighterType, echo-style fighter of Marth in Super Smash Bros.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fighterType Context triple: [Lucina, fighterType, echo-style fighter of Marth in Super Smash Bros.]
-
A.
fighter1
Indicates that the subject is the first participant or primary combatant in a fight or competitive physical confrontation.
-
B.
fleetType
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
C.
mainFighterAircraft
Indicates that an aircraft serves as the primary fighter aircraft for a given country, organization, or military force.
-
D.
fighter2
Indicates that the subject is the second participant (opponent) in a fighting or combat relationship or event.
-
E.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad593f88190a1e534fed38b3cd7 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b11124c8190babacf2a0fe2d057 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:37 p.m.