Triple
T24484157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White House tennis court |
E617459
|
entity |
| Predicate | hasNet |
P156479
|
FINISHED |
| Object | tennis net |
—
|
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: tennis net | Statement: [White House tennis court, hasNet, tennis net]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNet Context triple: [White House tennis court, hasNet, tennis net]
-
A.
hasIP
Indicates that one entity possesses, is assigned, or is associated with a specific IP address.
-
B.
hasNetworkUS
Indicates that an entity possesses, operates, or is associated with a network located in or serving the United States.
-
C.
hasPrimaryNetwork
Indicates that an entity is associated with or connected to its main or most important network among potentially multiple networks.
-
D.
netWork
Indicates a relationship where entities are connected or interact within a shared system, structure, or set of links that enables communication or exchange.
-
E.
hasNotableNetwork
Indicates that one entity is recognized for having a significant, influential, or widely connected network or set of relationships with other entities.
- 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_69e2d7f3ae788190b683394db15f220e |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a9d795288190916368e3cec1f666 |
completed | April 30, 2026, 1:01 a.m. |
Created at: April 18, 2026, 2:21 a.m.