Triple
T18040001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Koepp |
E431622
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Melissa Thomas |
—
|
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: Melissa Thomas | Statement: [David Koepp, spouse, Melissa Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Thomas Context triple: [David Koepp, spouse, Melissa Thomas]
-
A.
Melissa Thomas
chosen
Melissa Thomas is known as the wife of American screenwriter and director David Koepp.
-
B.
Melissa Robinson
Melissa Robinson is a key supporting character in the comedy film "Ace Ventura: Pet Detective," serving as a competent and skeptical ally to the eccentric detective Ace Ventura.
-
C.
Melissa Rycroft
Melissa Rycroft is an American television personality and former Dallas Cowboys Cheerleader best known for her appearances on reality shows such as The Bachelor and Dancing with the Stars.
-
D.
Melissa Blake
Melissa Blake is a television writer and producer known for her work on series such as "Heroes" and "Ghost Whisperer."
-
E.
Melissa Burns
Melissa Burns is known as the former spouse of American actor Jere Burns.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bfece6448190b4ba96075715bcef |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 10:25 a.m.