Triple
T442206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gisele Bündchen |
E10135
|
entity |
| Predicate | featuredOnCoverOf |
P997
|
FINISHED |
| Object | Time |
E800
|
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: Time | Statement: [Gisele Bündchen, featuredOnCoverOf, Time]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Time Context triple: [Gisele Bündchen, featuredOnCoverOf, Time]
-
A.
Time
chosen
Time is a major American news magazine known for its influential coverage of current events, politics, and culture.
-
B.
HyTime
HyTime is an SGML-based standard for representing and managing hypermedia and time-based multimedia structures in a platform-independent way.
-
C.
Time editors
Time editors are the editorial staff of Time magazine responsible for making major journalistic decisions, including choosing the annual Time Person of the Year.
-
D.
This Time
"This Time" is a song featured on the album "Evolver" by the Christian rock band John Legend.
-
E.
Press for Time
Press for Time is a 1966 British comedy film starring Norman Wisdom as a bumbling newspaper reporter whose chaotic antics cause widespread mayhem in a small seaside town.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f01d8fa88190849d720b029db479 |
completed | Feb. 28, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a43e73555481909fc972eed3337945 |
completed | March 1, 2026, 1:26 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.