Triple
T12236024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas McKean |
E291593
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Ann McKean |
E291593
|
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: Ann McKean | Statement: [Thomas McKean, child, Ann McKean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ann McKean Context triple: [Thomas McKean, child, Ann McKean]
-
A.
Ann McKean
chosen
Ann McKean was a daughter of Thomas McKean, a prominent American Founding Father and signer of the Declaration of Independence.
-
B.
Rachel McCleary
Rachel McCleary is an American economist and scholar known for her work on the intersection of religion, culture, and economic development.
-
C.
Anne MacKee
Anne MacKee is a character from the long-running British science fiction series "Doctor Who," appearing in stories involving the Doctor.
-
D.
Carolyn McCormick
Carolyn McCormick is an American actress best known for her recurring role as Dr. Elizabeth Olivet on the television series "Law & Order."
-
E.
Kate McKay
Kate McKay is the ambitious, modern-day career woman and romantic lead portrayed by Meg Ryan in the time-travel romantic comedy film "Kate & Leopold."
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb2892c81909a97b3ad6ec2c21b |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc30d72588190a1ebab7477c9e668 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 8, 2026, 9:51 p.m.