Triple
T11333181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stan Lynch |
E268400
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Stan |
E898984
|
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: Stan | Statement: [Stan Lynch, givenName, Stan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Context triple: [Stan Lynch, givenName, Stan]
-
A.
Stan
"Stan" is a critically acclaimed song by Eminem that tells the dark, narrative-driven story of an obsessive fan through a series of letters.
-
B.
Stan
Stan is a fast-talking, over-the-top used-boat and later used-coffin salesman known for his loud jacket and relentless sales pitches in the Monkey Island adventure game series.
-
C.
Stan
chosen
Stan is a probabilistic programming language and platform widely used for Bayesian statistical modeling and inference, particularly via methods like Hamiltonian Monte Carlo.
-
D.
Steve
Steve is a character best known as the calculating antagonist and betrayer in the heist film "The Italian Job."
-
E.
Steve
Steve is a central white homeowner character in the play "Clybourne Park," often embodying the tensions and awkward defenses of privilege in the story’s exploration of race and gentrification.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9fe5d5881908d786b212a554d8b |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5263160548190adb7d5c0fd6af0e2 |
completed | April 19, 2026, 7 p.m. |
Created at: April 8, 2026, 9:33 p.m.