Triple
T16438056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dammit |
E399225
|
entity |
| Predicate | chronologyNextSingle |
P2686
|
FINISHED |
| Object | Josie |
E774177
|
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: Josie | Statement: [Dammit, chronologyNextSingle, Josie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Josie Context triple: [Dammit, chronologyNextSingle, Josie]
-
A.
Josie
chosen
Josie is a common feminine given name, typically used as a diminutive form of Josephine.
-
B.
Susie
Susie is a recurring character from the animated television series "Family Guy," known as the infant daughter of Joe and Bonnie Swanson.
-
C.
Susie
Susie is a person whose full name is Susie Fairfield Dryden.
-
D.
Susie
Susie is a common diminutive or nickname for the female given name Susanna.
-
E.
Josie Packard
Josie Packard is a mysterious and enigmatic businesswoman in the television series "Twin Peaks," known for her complex relationships and hidden motives surrounding the town's lumber mill.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ba5a4748190b63ff53bfb5957c7 |
completed | April 18, 2026, 6:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0058143cb88190943b951cc8e47a66 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:10 a.m.