Triple
T19198653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M.T.A. |
E470039
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Charlie
Charlie is the hapless subway rider protagonist of the folk song "M.T.A.," doomed to ride Boston’s transit system forever because he lacks the fare to exit.
|
E89621
|
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: Charlie | Statement: [M.T.A., mainCharacter, Charlie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie Context triple: [M.T.A., mainCharacter, Charlie]
-
A.
Charlie
Charlie is the ambitious New York City hustler and small-time crook who serves as the central protagonist in the crime drama film "The Pope of Greenwich Village."
-
B.
Charlie
Charlie is a fictional character portrayed by American actor Jared Rushton, best known for his roles in late-1980s films.
-
C.
Charlie
Charlie is a person whose full name is Charlie Watson.
-
D.
Charlie
Charlie is the central protagonist in the romantic film "Love, Wedding, Marriage," around whom the story’s relationship and marital themes revolve.
-
E.
Charlie
Charlie is a fictional character who serves as the central figure in the story "The Winner."
- 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: Charlie Triple: [M.T.A., mainCharacter, Charlie]
Generated description
Charlie is the hapless subway rider protagonist of the folk song "M.T.A.," doomed to ride Boston’s transit system forever because he lacks the fare to exit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charlie Target entity description: Charlie is the hapless subway rider protagonist of the folk song "M.T.A.," doomed to ride Boston’s transit system forever because he lacks the fare to exit.
-
A.
Charlie
chosen
Charlie is the fictional Boston subway rider in the folk song "Charlie on the MTA," known for being unable to get off the train because he lacks the fare to exit.
-
B.
Charlie
Charlie is the ambitious New York City hustler and small-time crook who serves as the central protagonist in the crime drama film "The Pope of Greenwich Village."
-
C.
Charlie
Charlie is a person whose full name is Charlie Watson.
-
D.
Charlie
Charlie is a fictional character who serves as the central figure in the story "The Winner."
-
E.
Charlie
Charlie is a fictional character from Stephen Adly Guirgis’s gritty stage play "In Arabia We’d All Be Kings," which portrays the lives of struggling New Yorkers in a rapidly gentrifying Hell’s Kitchen.
- F. None of above.
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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a8daac8190b3558a1388596fb0 |
completed | April 20, 2026, 9:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a06f8c2805c8190be95a283c7db864f |
completed | May 15, 2026, 10:43 a.m. |
| NEDg | Description generation | batch_6a06f948932c8190a4ce08178c00b251 |
completed | May 15, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a06f9e1fb708190958c64fd38d32d04 |
completed | May 15, 2026, 10:48 a.m. |
Created at: April 10, 2026, 12:07 p.m.