Triple
T26616248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hooke Park campus |
E668067
|
entity |
| Predicate | hasMaterialFocus |
P193770
|
FINISHED |
| Object | timber |
—
|
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: timber | Statement: [Hooke Park campus, hasMaterialFocus, timber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaterialFocus Context triple: [Hooke Park campus, hasMaterialFocus, timber]
-
A.
hasCharacterFocus
Indicates that a work, scene, or segment centers primarily on a particular character’s experiences, perspective, or development.
-
B.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
C.
hasFocusText
Indicates that one entity provides the primary or highlighted textual content associated with another entity.
-
D.
hasValueFocus
Indicates that a particular value or data item is the primary focus or point of emphasis within a given context or relationship.
-
E.
hasVisualFocus
Indicates that one entity is currently directing its visual attention or gaze toward another entity.
- 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_69ee9cfe16088190a3dddd68e3c7b1ea |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
| PDg | Predicate description generation | batch_69fd553c01488190b9fda48b4a728f04 |
completed | May 8, 2026, 3:15 a.m. |
Created at: April 27, 2026, 2:19 a.m.