Triple
T18989995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kings Park Honour Avenues |
E464655
|
entity |
| Predicate | hasPlaquePlacement |
P134050
|
FINISHED |
| Object | at the base of each memorial tree |
—
|
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: at the base of each memorial tree | Statement: [Kings Park Honour Avenues, hasPlaquePlacement, at the base of each memorial tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaquePlacement Context triple: [Kings Park Honour Avenues, hasPlaquePlacement, at the base of each memorial tree]
-
A.
hasPlaque
Indicates that an entity possesses or displays a plaque, such as a commemorative plate or a deposit on a surface.
-
B.
hasNumberOfPlaques
Indicates the relationship that specifies how many plaques are associated with a given entity.
-
C.
hasPlaqueTextTopic
Indicates that the topic specified is the subject or main theme of the text written on a plaque.
-
D.
hasLanguageOnPlaque
Indicates that a specific language appears in the text or inscription displayed on a particular plaque.
-
E.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
- 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6632cb08190a28f6ab74c2156d8 |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f88e0c81908cb20f08bf24cd32 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:01 p.m.