Triple
T22064994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Rooters |
E545245
|
entity |
| Predicate | anthem |
P249
|
FINISHED |
| Object | Tessie |
—
|
NE NERFINISHED |
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: Tessie | Statement: [Royal Rooters, anthem, Tessie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessie Context triple: [Royal Rooters, anthem, Tessie]
-
A.
Tessie
Tessie is one of the young orphan girls in the musical "Annie," known for her anxious personality and frequent cries of "Oh my goodness, oh my goodness!"
-
B.
Tessie
chosen
Tessie is a Boston Red Sox mascot character, often depicted as a green monster and associated with Wally the Green Monster.
-
C.
Tessie
Tessie is a fictional character appearing in the story "The Silver Slipper."
-
D.
Tessie Hutchinson
Tessie Hutchinson is the central character in Shirley Jackson’s short story “The Lottery,” known for becoming the scapegoated victim of the town’s brutal annual ritual.
-
E.
Tess Goode
Tess Goode is a thoughtful, idealistic young woman in Wendy Wasserstein’s play "The Sisters Rosensweig," whose political convictions and generational perspective contrast with those of her mother and aunts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12882ab3c819095b61e0a341edfdf |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:27 p.m.