Triple
T13109470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hacks |
E310932
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Mark Indelicato |
E1109079
|
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: Mark Indelicato | Statement: [Hacks, starring, Mark Indelicato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Indelicato Context triple: [Hacks, starring, Mark Indelicato]
-
A.
Mark Indelicato
chosen
Mark Indelicato is an American actor and singer best known for his role as Justin Suarez on the television series "Ugly Betty."
-
B.
Tony DeMarco
Tony DeMarco was an American professional boxer and former world welterweight champion known for his aggressive, crowd-pleasing fighting style during the 1950s.
-
C.
Rick DiGiallonardo
Rick DiGiallonardo is a musician best known as a member of the American rock band Quarterflash.
-
D.
John DiFronzo
John DiFronzo was an American mobster who rose to become a powerful boss of the Chicago Outfit and a prominent figure in organized crime.
-
E.
Frank Santillo
Frank Santillo was an American film editor known for his work on numerous Hollywood productions, including classic Westerns.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817ce07881909ec552bf861ac175 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bba60c8819087b614cea03eb078 |
completed | May 9, 2026, 1:19 a.m. |
Created at: April 9, 2026, 9:05 p.m.