Triple
T8860823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Elizondo |
E210881
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | P!nk |
E75990
|
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: P!nk | Statement: [Mike Elizondo, workedWith, P!nk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: P!nk Context triple: [Mike Elizondo, workedWith, P!nk]
-
A.
Pink
Pink is a light, reddish color often associated with softness, romance, and playfulness.
-
B.
Pink
chosen
Pink is an American pop-rock singer and songwriter known for her powerful vocals, acrobatic live performances, and hits such as "Just Give Me a Reason" and "So What."
-
C.
Katy Perry
Katy Perry is an American pop singer and songwriter known for chart-topping hits like "Firework" and "Roar" and her colorful, theatrical performances.
-
D.
Kristina Pink
Kristina Pink is an American sports reporter best known for her work as an NFL and NBA sideline reporter on national television broadcasts.
-
E.
Stefani
Stefani is a prominent peak within Greece’s Mount Olympus massif, known for its striking rocky summit and dramatic alpine scenery.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e860888190a8a8702377db949e |
completed | April 1, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0b94f5481909902b5fa405a502f |
completed | April 3, 2026, 11:12 a.m. |
Created at: March 30, 2026, 6:50 p.m.