Triple
T11421665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Fortensky |
E270635
|
entity |
| Predicate | weddingCostEstimate |
P4259
|
FINISHED |
| Object | approximately $1.5 million |
—
|
LITERAL 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: approximately $1.5 million | Statement: [Larry Fortensky, weddingCostEstimate, approximately $1.5 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingCostEstimate Context triple: [Larry Fortensky, weddingCostEstimate, approximately $1.5 million]
-
A.
weddingCity
Indicates the city where a wedding takes place or is held.
-
B.
estimatedCost
chosen
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
C.
nuptialFlightTrigger
Indicates the condition or event that initiates or triggers a nuptial flight between mating individuals.
-
D.
nuptialFlightSeason
Indicates the time period during which nuptial flights (mating flights) occur for a given species.
-
E.
guestAtWedding
Indicates that a person is attending or has attended a particular wedding as a guest.
- F. None of above.
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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b357e88190ace56d36a945688f |
completed | April 9, 2026, 7:44 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.