Triple
T14929194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Hampshire Route 119 |
E372211
|
entity |
| Predicate | followsNear |
P61362
|
FINISHED |
| Object | Massachusetts border |
—
|
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: Massachusetts border | Statement: [New Hampshire Route 119, followsNear, Massachusetts border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsNear Context triple: [New Hampshire Route 119, followsNear, Massachusetts border]
-
A.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
B.
followsMoreClosely
Indicates that one entity follows another with a smaller distance, delay, or deviation than some alternative or reference follower.
-
C.
followsFace
Indicates that one entity adjusts its position or orientation to continuously track and remain aligned with another entity’s face.
-
D.
followsTo
Indicates that one entity moves or proceeds behind another entity toward a specific destination or target.
-
E.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded634e67881909daec9eaef188d09 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:36 a.m.