Triple
T36916751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Tiba |
E913063
|
entity |
| Predicate | urbanPolicyObjective |
P159355
|
FINISHED |
| Object | reduce pressure on existing urban centers |
—
|
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: reduce pressure on existing urban centers | Statement: [New Tiba, urbanPolicyObjective, reduce pressure on existing urban centers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanPolicyObjective Context triple: [New Tiba, urbanPolicyObjective, reduce pressure on existing urban centers]
-
A.
cityPolicy
Indicates a relationship where a city establishes or is governed by a specific policy, rule, or regulatory framework.
-
B.
urbanPolicyRole
Indicates a role or responsibility that an entity has in shaping, implementing, or influencing urban policy.
-
C.
urbanDesignGoal
Indicates a goal or intended outcome related to the planning, shaping, or improvement of urban spaces and environments.
-
D.
typeOfUrbanPolicy
Indicates the specific category or kind of urban policy that characterizes or governs a given urban-related entity or action.
-
E.
urbanDevelopmentGoal
chosen
Indicates a targeted objective or desired outcome related to the planning, growth, or improvement of urban areas.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55ad44bc8190a802bdaab36adc94 |
completed | May 6, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.