Triple
T150698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clementine Ogilvy Hozier |
E3424
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Clementine |
E3423
|
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: Clementine | Statement: [Clementine Ogilvy Hozier, givenName, Clementine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clementine Context triple: [Clementine Ogilvy Hozier, givenName, Clementine]
-
A.
Clementine
chosen
Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
-
B.
Malus
Malus is a genus of deciduous trees and shrubs in the rose family best known for cultivated apples and ornamental crabapples.
-
C.
Coolamon
Coolamon is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural heritage and historic streetscape.
-
D.
Rosa
Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
-
E.
Lick
Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c93bbd508190b81527bd95c6e5f4 |
completed | Feb. 28, 2026, 10:53 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.