Triple
T2484426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Lindros |
E55890
|
entity |
| Predicate | notable issue |
P9106
|
FINISHED |
| Object | concussion history |
—
|
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: concussion history | Statement: [Eric Lindros, notable issue, concussion history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notable issue Context triple: [Eric Lindros, notable issue, concussion history]
-
A.
hasNotableIssue
chosen
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
notableResolution
Indicates that an entity is distinguished or recognized for having a particularly important, impactful, or well-known resolution or decision.
-
C.
notableReport
Indicates that an entity has produced, authored, or is otherwise associated with a report that is considered notable or significant.
-
D.
notableDuring
Indicates that something was especially prominent, active, or significant during a particular time period or event.
-
E.
knownIssue
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.