Triple
T38658693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circumferential Road 5 |
E939968
|
entity |
| Predicate | sequenceInSystem |
P117777
|
FINISHED |
| Object | fifth circumferential road of Metro Manila |
—
|
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: fifth circumferential road of Metro Manila | Statement: [Circumferential Road 5, sequenceInSystem, fifth circumferential road of Metro Manila]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sequenceInSystem Context triple: [Circumferential Road 5, sequenceInSystem, fifth circumferential road of Metro Manila]
-
A.
sequenceInEvent
Indicates that one event occurs as a specific step or ordered part within a larger, encompassing event.
-
B.
sequenceInCategory
chosen
Indicates that one entity occurs as an ordered element within a specific category or grouping of items.
-
C.
sequenceID
Indicates that an entity is associated with a specific position or identifier within an ordered sequence.
-
D.
sequenceInWork
Indicates that one work appears as a sequential part or installment within a larger overarching work.
-
E.
sequenceInField
Indicates that one entity occurs as an ordered sequence within the context, scope, or domain defined by another entity (the field).
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.