Triple
T3996337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lily Allen |
E87106
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lily |
E52031
|
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: Lily | Statement: [Lily Allen, givenName, Lily]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lily Context triple: [Lily Allen, givenName, Lily]
-
A.
Lily
chosen
Lily is a feminine given name of English origin commonly associated with the lily flower and symbolizing purity and beauty.
-
B.
Lily
Lily is a pivotal character in the psychological thriller film "Black Swan," serving as a seductive and enigmatic rival whose presence intensifies the protagonist's descent into paranoia and self-destruction.
-
C.
Lilly
Lilly is the surname of Bob Lilly, a Pro Football Hall of Fame defensive tackle best known for his career with the Dallas Cowboys.
-
D.
Lily Bell
Lily Bell is a central character in the television series "Hell on Wheels," portrayed as a determined and resourceful Englishwoman navigating the dangers and politics surrounding the construction of the transcontinental railroad.
-
E.
Lillie
Lillie is the given name of Lillie Hitchcock Coit, a famed 19th-century San Francisco socialite and patron associated with the city’s firefighting history.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa2159d88190a01de8b038341916 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5403f14ec8190a77189c7066676f2 |
completed | March 14, 2026, 11:02 a.m. |
Created at: March 9, 2026, 3:34 p.m.