Triple
T4375084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Oaks |
E98984
|
entity |
| Predicate | featureHighlighted |
P3362
|
FINISHED |
| Object | abundance of oak trees |
—
|
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: abundance of oak trees | Statement: [City of Oaks, featureHighlighted, abundance of oak trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureHighlighted Context triple: [City of Oaks, featureHighlighted, abundance of oak trees]
-
A.
featuredArea
Indicates that an area or section is highlighted or given special prominence within a larger context or layout.
-
B.
featuresStar
Indicates that one entity prominently includes or showcases another entity as a main star or featured performer.
-
C.
featuresHero
Indicates that something (such as a work, product, or story) prominently includes or centers around a particular hero as a main character or focus.
-
D.
highlights
chosen
Indicates that one entity draws special attention to, emphasizes, or visually marks another entity as important or noteworthy.
-
E.
specialFeature
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352222df48190bead639e99635faf |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.