Triple
T36816363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sants-Montjuïc |
E909749
|
entity |
| Predicate | hasNotablePortArea |
P64085
|
FINISHED |
| Object | Port of Barcelona |
E52269
|
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: Port of Barcelona | Statement: [Sants-Montjuïc, hasNotablePortArea, Port of Barcelona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotablePortArea Context triple: [Sants-Montjuïc, hasNotablePortArea, Port of Barcelona]
-
A.
hasPortArea
chosen
Indicates that an entity possesses or is associated with a specific port area, typically representing the spatial extent or boundary of its port facilities.
-
B.
hasNotablePortTown
Indicates that an entity possesses or is associated with a town known for its significant or prominent port.
-
C.
hasPorts
Indicates that an entity is equipped with or provides access points (ports) for connection, communication, or interface with other entities or systems.
-
D.
hasMajorPort
Indicates that a location possesses a primary, significant seaport used for major commercial or transportation activities.
-
E.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
- F. None of above.
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_69f76e7dd13c81908c60b05adb49eeb5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3dde5f21648190aa278d9c91a09f91 |
completed | June 26, 2026, 2:05 a.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.