Triple
T53994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HTTP |
E1064
|
entity |
| Predicate | portNumber |
P2548
|
FINISHED |
| Object | 80 |
—
|
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: 80 | Statement: [HTTP, portNumber, 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portNumber Context triple: [HTTP, portNumber, 80]
-
A.
port
Indicates a relationship where one entity serves as a harbor, access point, or interface through which another entity can enter, exit, or connect.
-
B.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
C.
serviceNumber
Indicates a unique identifying number assigned to a service, used to reference, track, or distinguish that service from others.
-
D.
hasMajorPort
Indicates that a location possesses a primary, significant seaport used for major commercial or transportation activities.
-
E.
majorPortAtMouth
Indicates that a major port is located at the mouth of a river where it meets a larger body of water.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b39eef081909cec4333f2b25513 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.