Triple
T12991109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress |
E321906
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Ice |
E814070
|
NE 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: Ice | Statement: [Empress, hasTrack, Ice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ice Context triple: [Empress, hasTrack, Ice]
-
A.
Ice
Ice is a television drama series featuring Cam Gigandet in a central role, set in the high-stakes world of the diamond trade.
-
B.
Ice
chosen
"Ice" is a song by Canadian singer-songwriter Sarah McLachlan from her acclaimed 1993 album *Fumbling Towards Ecstasy*.
-
C.
Ice
Ice is the massive Valyrian steel greatsword of House Stark, famously wielded by Eddard Stark in the world of "A Song of Ice and Fire" and its TV adaptation "Game of Thrones."
-
D.
ICE
ICE is a U.S. federal agency under the Department of Homeland Security responsible for enforcing immigration laws and investigating customs, border, and national security-related offenses.
-
E.
ICE
ICE is Emirates’ award-winning in-flight entertainment system offering a wide range of movies, TV, music, and information services to passengers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0fca5e4819086b010fdd1813419 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:43 p.m.