Triple
T5918931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Daley |
E131652
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Maggie |
E103868
|
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: Maggie | Statement: [Maggie Daley, nickname, Maggie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maggie Context triple: [Maggie Daley, nickname, Maggie]
-
A.
Maggie
chosen
Maggie is a common diminutive form of the given name Margaret, often used as a familiar or affectionate nickname.
-
B.
Maggie
Maggie is a character portrayed by Australian actress Robin McLeavy, best known from the horror film "The Loved Ones."
-
C.
Maggie
Maggie is a central character in the 1992 British ensemble comedy-drama film "Peter’s Friends," which follows a group of Cambridge university friends reuniting after a decade.
-
D.
Maggie Pierce
Maggie Pierce is a cardiothoracic surgeon and the biological half-sister of Meredith Grey on the long-running medical drama series Grey’s Anatomy.
-
E.
Maggie Seaver
Maggie Seaver is a central character on the sitcom "Growing Pains," portrayed as a working mother balancing her journalism career with raising her family.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c038003c408190b2a89df0b759dcbf |
completed | March 22, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c03a95688190bfd51d7ada1e538f |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 4 p.m.