Triple
T14029972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grassy Park |
E337560
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Ottery |
E884211
|
NE 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: Ottery | Statement: [Grassy Park, locatedNear, Ottery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ottery Context triple: [Grassy Park, locatedNear, Ottery]
-
A.
Ottery
chosen
Ottery is a residential suburb located in the Southern Suburbs region of Cape Town, South Africa.
-
B.
Ottery St Mary
Ottery St Mary is a historic town in Devon, England, known for its picturesque setting on the River Otter and its associations with poet Samuel Taylor Coleridge.
-
C.
Otterbourne
Otterbourne is a village in Hampshire, England, situated near Winchester and known for its rural character and historic parish church.
-
D.
Bunnyburrow
Bunnyburrow is a rural, rabbit-populated farming community in Disney's Zootopia universe and the childhood home of protagonist Judy Hopps.
-
E.
Otterberg
Otterberg is a small historic town in the Rhineland-Palatinate region of western Germany, known for its former Cistercian abbey and medieval architecture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa9f8248190930954d609dee5f1 |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc335a474819084c310b10e0ded9a |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.