Triple
T21095656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carole E. Barrowman |
E519758
|
entity |
| Predicate | coAuthorOf |
P2389
|
FINISHED |
| Object | I Am What I Am |
—
|
NE NERFINISHED |
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: I Am What I Am | Statement: [Carole E. Barrowman, coAuthorOf, I Am What I Am]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Am What I Am Context triple: [Carole E. Barrowman, coAuthorOf, I Am What I Am]
-
A.
I Am What I Am
"I Am What I Am" is a popular show tune from the musical La Cage aux Folles that has become an anthem of self-acceptance and LGBTQ+ pride.
-
B.
I Am What I Am
chosen
"I Am What I Am" is an autobiographical work co-written by actor John Barrowman and his sister Carole E. Barrowman, detailing his life, career, and experiences as an openly gay entertainer.
-
C.
I Am What I Am
"I Am What I Am" is a self-expressive, individuality-focused advertising slogan used by the athletic footwear and apparel company Reebok.
-
D.
I Am What I Am
"I Am What I Am" is a studio album by Welsh singer Shirley Bassey, featuring her powerful interpretations of popular standards and show tunes.
-
E.
“I Am What I Am”
“I Am What I Am” is a song featured within the musical work or album “Green Man.”
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b5845f88190a16f3df157f0906c |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:52 p.m.