Triple
T13993073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Like It |
E336628
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Sam Watters |
E632686
|
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: Sam Watters | Statement: [I Like It, writer, Sam Watters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Watters Context triple: [I Like It, writer, Sam Watters]
-
A.
Sam Watters
chosen
Sam Watters is an American songwriter and record producer best known as a member of the 1990s R&B group Color Me Badd and for writing and producing hits for artists like Jessica Simpson, Kelly Clarkson, and Anastacia.
-
B.
Mark Wareham
Mark Wareham is an Australian cinematographer known for his work on feature films and television, including "The Drover’s Wife: The Legend of Molly Johnson."
-
C.
Michael Watts
Michael Watts is a notable individual whose name is associated with the surname Watts, though additional context is needed to distinguish his specific identity or achievements.
-
D.
Andrew Watts
Andrew Watts is a British countertenor known for his performances in contemporary opera and concert repertoire.
-
E.
Chris Barwell
Chris Barwell is a film editor known for his work on the 2018 action-adventure movie "Robin Hood."
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb3b5d881909f15a1e08bb202f3 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac9a7e8c8190a0fd0cd67ff50741 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.