Triple
T13488056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tenable |
E318556
|
entity |
| Predicate | hasLifelinesOrAssists |
P110593
|
FINISHED |
| Object | team support and passes in some rounds |
—
|
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: team support and passes in some rounds | Statement: [Tenable, hasLifelinesOrAssists, team support and passes in some rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLifelinesOrAssists Context triple: [Tenable, hasLifelinesOrAssists, team support and passes in some rounds]
-
A.
wasAssistedBy
Indicates that an entity carried out an action or achieved a result with the help or support of another entity.
-
B.
assistsWith
Indicates that one entity helps or supports another entity in performing or accomplishing a specific task, activity, or objective.
-
C.
assistsOver
Indicates that one entity provides help or support to another entity in a way that surpasses or exceeds a certain reference level, standard, or counterpart.
-
D.
hasLifesavers
Indicates that one entity possesses or is associated with lifesavers (such as life-preserving devices or aids).
-
E.
scoredAssists
Indicates that one entity contributed an assist that led to another entity scoring (typically in a game or sports context).
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3b9b488190bb4e11424ff599c8 |
completed | April 12, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:42 p.m.