Triple
T27501928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medal of Honor: Airborne score |
E694176
|
entity |
| Predicate | countryOfOriginOfGame |
P26
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Medal of Honor: Airborne score, countryOfOriginOfGame, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfOriginOfGame Context triple: [Medal of Honor: Airborne score, countryOfOriginOfGame, United States]
-
A.
countryOfGameOrigin
Indicates the country where a game was originally created, developed, or first produced.
-
B.
countryOfOrigin
chosen
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
C.
placeOfOrigin
Indicates the location or source from which an entity originally comes or was created.
-
D.
countryOfDeveloper
Indicates the country in which the developer of an entity (such as a product, software, or work) is based or originates.
-
E.
gameOfOrigin
Indicates the game from which an entity, such as a character, item, or concept, originally comes.
- 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_69ef538370888190b1ddf53bb4831188 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fd4f39b5008190b83b3227ce22c509 |
completed | May 8, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69fd4df17c548190a4e2a6fea70f7e10 |
completed | May 8, 2026, 2:44 a.m. |
Created at: April 27, 2026, 1:11 p.m.