Triple
T11546615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Hawk |
E273789
|
entity |
| Predicate | firstToLand |
P100039
|
FINISHED |
| Object | 900 on a skateboard in competition |
—
|
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: 900 on a skateboard in competition | Statement: [Tony Hawk, firstToLand, 900 on a skateboard in competition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstToLand Context triple: [Tony Hawk, firstToLand, 900 on a skateboard in competition]
-
A.
firstLandingBy
Indicates that one entity is the earliest or initial instance to arrive, land, or touch down at a particular place or target relative to others.
-
B.
firstFlightLandingSite
Indicates the location where an aircraft or spacecraft completes its initial flight by landing.
-
C.
firstEuropeanLandingDate
Indicates the date on which Europeans first arrived at or made landfall in a particular place.
-
D.
firstFlight
Indicates that the associated event or record corresponds to the earliest or initial flight taken or performed by the referenced entity.
-
E.
firstChartedOn
Indicates that an entity was first mapped, recorded, or charted on a specific date or during a specific time.
- F. None of above. chosen
Provenance (4 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d886e3ad548190b2c88332f5d919bd |
completed | April 10, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69d8087cbe7c819085680f3d67ccc978 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822f00a088190ac6b48e45e743899 |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:37 p.m.