Triple
T7357999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trajan Langdon |
E169673
|
entity |
| Predicate | laterWorkedFor |
P11675
|
FINISHED |
| Object | Brooklyn Nets front office |
—
|
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: Brooklyn Nets front office | Statement: [Trajan Langdon, laterWorkedFor, Brooklyn Nets front office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterWorkedFor Context triple: [Trajan Langdon, laterWorkedFor, Brooklyn Nets front office]
-
A.
hasWorkedFor
chosen
Indicates that an entity has been employed by or has provided work or services to another entity.
-
B.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
C.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
D.
laterWorkBy
Indicates that one work was created after another work by the same creator or author.
-
E.
laterWork
Indicates that one work was created, published, or produced after another work in time.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f02d36108190bcb34a95e6a30bd7 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:06 p.m.