Triple
T23944629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Post-it Notes |
E602880
|
entity |
| Predicate | hasAdhesiveType |
P154443
|
FINISHED |
| Object | pressure-sensitive adhesive |
—
|
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: pressure-sensitive adhesive | Statement: [Post-it Notes, hasAdhesiveType, pressure-sensitive adhesive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdhesiveType Context triple: [Post-it Notes, hasAdhesiveType, pressure-sensitive adhesive]
-
A.
coatingType
Indicates the type or kind of coating applied to or associated with an entity.
-
B.
hasPeelType
Indicates the type or characteristic of the outer peel or skin associated with an entity.
-
C.
hasCushionType
Indicates that an entity is associated with or equipped with a specific type of cushion.
-
D.
isThickenedWith
Indicates that one substance has been made more viscous or dense by adding another substance that serves as a thickening agent.
-
E.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
- 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_69e2953e4924819093f1c24c03476b42 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d02d07b08190acbcbb646cd9a58e |
completed | April 29, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:11 p.m.