Triple
T9978251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NTLM |
E196384
|
entity |
| Predicate | commonlyUsedWhen |
P11801
|
FINISHED |
| Object | Kerberos is not available |
—
|
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: Kerberos is not available | Statement: [NTLM, commonlyUsedWhen, Kerberos is not available]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUsedWhen Context triple: [NTLM, commonlyUsedWhen, Kerberos is not available]
-
A.
oftenUsedAfter
Indicates that one entity is frequently or typically used immediately following another entity in a sequence or workflow.
-
B.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb84ef8ac8190abbe78b7611c5309 |
completed | April 2, 2026, 12:29 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:49 p.m.