Triple
T28841163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 493 |
E728317
|
entity |
| Predicate | numberingRole |
P200643
|
FINISHED |
| Object | auxiliary Interstate route number |
—
|
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: auxiliary Interstate route number | Statement: [Interstate 493, numberingRole, auxiliary Interstate route number]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberingRole Context triple: [Interstate 493, numberingRole, auxiliary Interstate route number]
-
A.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
B.
numberingReason
Indicates the rationale or basis for assigning a particular number or numbering scheme to something.
-
C.
hasNumberingRole
Indicates that an entity holds a specific role or responsibility related to assigning, managing, or using numbers within a given context.
-
D.
legalNumbering
Indicates that an entity has an officially assigned legal or regulatory identification number.
-
E.
numberingDirection
Indicates the direction or order in which items are sequentially numbered within a set or structure.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69ff9d9cb4f8819083682be3c483b599 |
completed | May 9, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69ff9c38bf9c8190bbb85b32f3ae3d2e |
completed | May 9, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69ff9d9ba1ac8190a0cca5764bb5904d |
completed | May 9, 2026, 8:48 p.m. |
Created at: April 28, 2026, 6:40 a.m.