Triple
T21235499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fortune rankings |
E523332
|
entity |
| Predicate | includesList |
P63353
|
FINISHED |
| Object | Fortune Unicorn List |
—
|
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: Fortune Unicorn List | Statement: [Fortune rankings, includesList, Fortune Unicorn List]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fortune Unicorn List Context triple: [Fortune rankings, includesList, Fortune Unicorn List]
-
A.
Fortunezen
Fortunezen are the supporters of the Dutch football club Fortuna Sittard.
-
B.
Lot of Fortune
Lot of Fortune is a key calculated point in Hellenistic astrology used to assess a person's material circumstances, bodily well-being, and general fortune in life.
-
C.
Fortunes
Fortunes is a collection of surrealist poems by French writer Robert Desnos, showcasing his imaginative, dreamlike style and playful use of language.
-
D.
Fortune
chosen
Fortune is a long-running American business magazine known for its influential rankings such as the Fortune 500 and in-depth coverage of global economics and corporate leadership.
-
E.
Fortune
"Fortune" is a song by British singer-songwriter Laura Marling from her critically acclaimed album "Song for Our Daughter."
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7351f0e988190bb77b598cb8a9532 |
completed | April 21, 2026, 8:28 a.m. |
Created at: April 16, 2026, 3:46 p.m.