Triple
T8904227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Clare |
E212009
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Too Close |
E766548
|
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: Too Close | Statement: [Alex Clare, notableSong, Too Close]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Too Close Context triple: [Alex Clare, notableSong, Too Close]
-
A.
Too Close
chosen
"Too Close" is a 2011 electro-soul song by British singer Alex Clare that gained widespread popularity after being featured in a major Internet Explorer commercial.
-
B.
So Close
So Close is a popular song by South Korean singer JR, recognized as one of his standout solo releases.
-
C.
Come Close
"Come Close" is a soulful hip-hop single by Common, produced by The Neptunes and known for its intimate, romantic lyrics.
-
D.
Come Closer
"Come Closer" is a hit Afrobeats single by Nigerian artist Wizkid featuring Drake, known for its fusion of Afrobeat and dancehall and its international chart success.
-
E.
Don’t Get Too Close
Don’t Get Too Close is a 2023 studio album by American electronic music producer Skrillex that blends dubstep, pop, and experimental electronic styles with numerous vocal collaborations.
- 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_69ca839255248190b43984294abd92ae |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc64c2509881908fb692522d348e96 |
completed | April 1, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1cb724c8190bc080d2a7f751e60 |
completed | April 3, 2026, 1:34 p.m. |
Created at: March 30, 2026, 6:55 p.m.