Triple
T10973566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Myers |
E259308
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Tony Moran
Tony Moran is an American actor best known for playing the unmasked Michael Myers in John Carpenter’s original 1978 horror film "Halloween."
|
E896828
|
NE FINISHED |
How this triple was built (4 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: Tony Moran | Statement: [Michael Myers, portrayedBy, Tony Moran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Moran Context triple: [Michael Myers, portrayedBy, Tony Moran]
-
A.
Joseph Moran
Joseph Moran was the husband of acclaimed American character actress Thelma Ritter.
-
B.
Nick Moran
Nick Moran is an English actor and filmmaker best known for his role in the crime comedy film "Lock, Stock and Two Smoking Barrels."
-
C.
Terry Moran
Terry Moran is an American journalist and television correspondent best known for his work with ABC News, including roles as a White House correspondent and co-anchor of "Nightline."
-
D.
Mickey Moran
Mickey Moran is the ambitious, idealistic teenager who leads a group of kids in putting on a show in the classic 1939 musical film "Babes in Arms."
-
E.
Don Murray
Don Murray is an American actor best known for his Oscar-nominated film debut in the 1956 drama "Bus Stop" opposite Marilyn Monroe.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tony Moran Triple: [Michael Myers, portrayedBy, Tony Moran]
Generated description
Tony Moran is an American actor best known for playing the unmasked Michael Myers in John Carpenter’s original 1978 horror film "Halloween."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tony Moran Target entity description: Tony Moran is an American actor best known for playing the unmasked Michael Myers in John Carpenter’s original 1978 horror film "Halloween."
-
A.
Joseph Moran
Joseph Moran was the husband of acclaimed American character actress Thelma Ritter.
-
B.
Nick Moran
Nick Moran is an English actor and filmmaker best known for his role in the crime comedy film "Lock, Stock and Two Smoking Barrels."
-
C.
Terry Moran
Terry Moran is an American journalist and television correspondent best known for his work with ABC News, including roles as a White House correspondent and co-anchor of "Nightline."
-
D.
Mickey Moran
Mickey Moran is the ambitious, idealistic teenager who leads a group of kids in putting on a show in the classic 1939 musical film "Babes in Arms."
-
E.
Don Murray
Don Murray is an American actor best known for his Oscar-nominated film debut in the 1956 drama "Bus Stop" opposite Marilyn Monroe.
- F. None of above. chosen
Provenance (5 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7719c16648190ab5a87abb1c61990 |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d7a0b3dc819084fbda3227caf5b5 |
completed | April 18, 2026, 1 a.m. |
| NEDg | Description generation | batch_69e2ff211ae88190a40380cd25a61812 |
completed | April 18, 2026, 3:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e32634397481908284c04448274b25 |
completed | April 18, 2026, 6:35 a.m. |
Created at: April 8, 2026, 9:24 p.m.