Triple
T14767496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Equalizer (1985 TV series) |
E347034
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Control (character)
Control is a recurring intelligence-agency superior and former colleague of Robert McCall in the 1985 television series "The Equalizer."
|
E1119156
|
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: Control (character) | Statement: [The Equalizer (1985 TV series), character, Control (character)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Control (character) Context triple: [The Equalizer (1985 TV series), character, Control (character)]
-
A.
Mii
Mii is a customizable avatar character created by players on Nintendo consoles and used across various games as a personal in-game representation.
-
B.
Luella Gear
Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
-
C.
Ness
Ness is a remote crofting and fishing community at the northern tip of the Isle of Lewis in Scotland’s Outer Hebrides.
-
D.
Ness
Ness is a small village in the civil parish of Neston on the Wirral Peninsula in Cheshire, England.
-
E.
Chi-Fu
Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
- 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: Control (character) Triple: [The Equalizer (1985 TV series), character, Control (character)]
Generated description
Control is a recurring intelligence-agency superior and former colleague of Robert McCall in the 1985 television series "The Equalizer."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Control (character) Target entity description: Control is a recurring intelligence-agency superior and former colleague of Robert McCall in the 1985 television series "The Equalizer."
-
A.
Mii
Mii is a customizable avatar character created by players on Nintendo consoles and used across various games as a personal in-game representation.
-
B.
Luella Gear
Luella Gear was an American actress and comedian known for her work in early 20th-century stage and film productions.
-
C.
Ness
Ness is a remote crofting and fishing community at the northern tip of the Isle of Lewis in Scotland’s Outer Hebrides.
-
D.
Ness
Ness is a small village in the civil parish of Neston on the Wirral Peninsula in Cheshire, England.
-
E.
Chi-Fu
Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81236f081908063bb4350b7b985 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf68d94819093567bc630f67b60 |
completed | May 8, 2026, 4:19 p.m. |
| NEDg | Description generation | batch_69fe1b0056988190b14560470428d895 |
completed | May 8, 2026, 5:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe1b97e8148190b23a555b9f2c7f1f |
completed | May 8, 2026, 5:21 p.m. |
Created at: April 10, 2026, 1:30 a.m.