Triple
T8319097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firestarter |
E194782
|
entity |
| Predicate | characterNickname |
P41555
|
FINISHED |
| Object |
Charlie
Charlie is the young girl with powerful pyrokinetic abilities at the center of Stephen King’s novel "Firestarter."
|
E725772
|
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: [Firestarter, characterNickname, Charlie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie Context triple: [Firestarter, characterNickname, Charlie]
-
A.
Charlie
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 Dory’s loving but forgetful father in the animated film "Finding Dory," known for his patience, optimism, and inventive ways of helping her cope with memory loss.
-
C.
Charlie
Charlie is the given name of the British philosopher and Cambridge academic C. D. Broad.
-
D.
Charlie
Charlie is the yellow-suited captain and one of the three main playable leaders in Pikmin 3, known for commanding Pikmin on the planet PNF-404.
-
E.
Charlie
Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
- 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: [Firestarter, characterNickname, Charlie]
Generated description
Charlie is the young girl with powerful pyrokinetic abilities at the center of Stephen King’s novel "Firestarter."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charlie Target entity description: Charlie is the young girl with powerful pyrokinetic abilities at the center of Stephen King’s novel "Firestarter."
-
A.
Charlie
Charlie is the central protagonist of the apocalyptic horror film "Legion" (2010), a pregnant waitress whose unborn child is believed to be humanity’s last hope.
-
B.
Charlie
Charlie is a character featured in the work titled "Seascape."
-
C.
Charlie
Charlie is a central character in the romantic comedy film "French Kiss," serving as the unfaithful fiancé whose actions set the story’s events in motion.
-
D.
Charlie
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.
-
E.
Charlie
"Charlie" is a 2022 pop album by American singer-songwriter Charlie Puth that showcases his hook-driven production and personal, introspective songwriting.
- 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_69ca82e7a8a88190a32bb5cc0feb012d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f648e10819081ad1fed870b2b86 |
completed | March 31, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd9596891c81909296050d0a8117ca |
completed | April 1, 2026, 10 p.m. |
| NEDg | Description generation | batch_69cdab5f30b0819080136084d81774a9 |
completed | April 1, 2026, 11:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdb2d365e48190a766ca959ce56b19 |
completed | April 2, 2026, 12:05 a.m. |
Created at: March 30, 2026, 5:55 p.m.