Triple
T18523927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luis Lopez-Fitzgerald |
E452664
|
entity |
| Predicate | romanticPartner |
P9994
|
FINISHED |
| Object | Fancy Crane |
—
|
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: Fancy Crane | Statement: [Luis Lopez-Fitzgerald, romanticPartner, Fancy Crane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fancy Crane Context triple: [Luis Lopez-Fitzgerald, romanticPartner, Fancy Crane]
-
A.
Fancy Crane
chosen
Fancy Crane is a fictional character from the soap opera "Passions," known as a wealthy and often scheming member of the Crane family.
-
B.
Auspicious Cranes
Auspicious Cranes is a renowned painting by the Song dynasty emperor-artist Huizong, celebrated for its elegant depiction of cranes and refined courtly style.
-
C.
Papercranes
Papercranes is an indie rock/folk music project led by musician and actress Rain Phoenix, known for its atmospheric, introspective sound.
-
D.
Crane
Crane is a small city in western Texas that serves as the administrative and economic center of Crane County, historically tied to the region’s oil industry.
-
E.
Crane
Crane is a character from the "Kung Fu Panda" franchise, depicted as a skilled, slender bird kung fu master and member of the Furious Five.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e533908b0c81908725baf828aa46ff |
completed | April 19, 2026, 7:57 p.m. |
Created at: April 10, 2026, 11:37 a.m.