Triple
T17948748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Harris |
E448772
|
entity |
| Predicate | hasStatusRelativeToGeorgeHarris |
P129852
|
FINISHED |
| Object | legal owner |
—
|
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: legal owner | Statement: [Mr. Harris, hasStatusRelativeToGeorgeHarris, legal owner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusRelativeToGeorgeHarris Context triple: [Mr. Harris, hasStatusRelativeToGeorgeHarris, legal owner]
-
A.
hasStatusBasedOn
Indicates that an entity’s status is determined or derived from another condition, event, or entity.
-
B.
JackSikmaStatus
Indicates the professional or career-related status or condition associated with Jack Sikma.
-
C.
hadSpecialStatusIn
Indicates that an entity possessed a particular special, exceptional, or non-standard status within a specified context or time period.
-
D.
hasStatusLabel
Indicates that an entity is associated with a specific status expressed as a human-readable label.
-
E.
hasHighPointStatus
Indicates that an entity holds a high or elevated status within a point-based or ranking system.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afaac780819097434b20b1f155d2 |
completed | April 19, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
| PDg | Predicate description generation | batch_69e42d8d68288190a05dc5d7803cf823 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:21 a.m.